# tessa – simple, hassle-free access to price information of financial assets

tessa is a Python library to help you **easily retrieve price information** for assets
from different sources such as Yahoo or Coingecko. It takes care of the different APIs,
caching, rate limiting, and other hassles.

tessa provides a **Symbol class that encapsulates the methods relevant for a symbol**.
tessa also provides functionality to **manage collections of symbols**, store and load
them, and extend their functionality.

Finally, tessa makes sure to be nice to the sites being accessed and tries to **prevent
users from being blocked by 429 rate limiting errors** by 1) caching results upon
retrieval and 2) keeping track of request timestamps and waiting appropriate amounts of
time if necessary. tessa also automatically waits and retries requests that fail with a
5xx error.

[→ Check out the full documentation. 📖](https://ymyke.github.io/tessa/tessa.html)

<img src="demo.gif" width="50%">


## How to use

Here's a longer example that shows all aspects of the library. Refer to
submodules [symbol](tessa/symbol.html), [search](tessa/search.html), and
[price](tessa/price.html) for more information.

###### Imports:

```python
from tessa import Symbol, SymbolCollection, search
import pendulum
```

###### Create a symbol for MSFT and access some functions:

```python
s1 = Symbol("MSFT")             # will use "yahoo" as the default source
s1.price_latest()               # get latest price
```

###### Create another symbol from a bloomberg ticker as it is used by Yahoo Finance:

```python
s2 = Symbol("SREN.SW")
s2.price_point("2022-06-30")    # get price at specific point in time
```

###### Create a symbol from the coingecko source with an id as it is used by coingecko:

```python
s3 = Symbol("bitcoin", source="coingecko")
s3.price_graph()                # show price graph
```

###### Search for a crypto ticker on coingecko:

```python
res = search("name")  # search and print search result summary
filtered = res.filter(source="coingecko")  # filter results
filtered.p()  # print summary of filtered results
filtered.buckets[1].symbols  # review the 2nd bucket in the filtered results
s4 = filtered.buckets[1].symbols[4]  # our symbol is the 5th in that list
s4.price_history()  # get entire history
s4.price_graph()  # visualize the price history
```

###### Build a collection of several symbols and use the collection to retrieve symbols:

```python
sc = SymbolCollection([s1, s2, s3, s4])   # create a collection w/ symbols from above
sc.add(Symbol("AAPL"))                    # add another one
sc.find_one("SREN").price_graph()
```

###### Store and load a symbol collection:

```python
sc.save_yaml("my_symbols.yaml")
sc_new = SymbolCollection()
sc_new.load_yaml("my_symbols.yaml")
```

###### Use a different currency preference:

```python
sc.find_one("ens").price_latest()   # will return price in USD
Symbol.currency_preference = "CHF"
sc.find_one("ens").price_latest()   # will return price in CHF
```

Note that `currency_preference` will only have an effect with sources that support it.
It is supported for Coingecko but not for Yahoo. So you should always verify the
effective currency you receive in the result.

On Yahoo, some tickers are listed in several currency-specific variants that you can
try:

```python
Symbol("ETH-USD").price_latest()  # will return the price in USD
Symbol("ETH-EUR").price_latest()  # will return the price in EUR
```

###### Accessing older crypto price information:

Coingecko only provides a limited amount of historical data:

```python
from_date = (pendulum.now() - pendulum.duration(months=6)).to_date_string()
Symbol("bitcoin", source="coingecko").price_point(from_date)
# Will work because coingecko has data for the last year
Symbol("bitcoin", source="coingecko").price_point("2020-08-01")
# Will result in a value error as the data is not available
```

Yahoo also lists a number of crypto assets with longer history, so you can try that
source as well:

```python
Symbol("BTC-USD").price_point(from_date)  # Should work, "yahoo" is the default source
```

###### `price_point` tries to be lenient and you can adjust the leniency:

By default, `price_point` will try to find the closest price to the requested date as
long as it's not more than `max_date_deviation_days` days away (default: 10 days).

```python
ea = Symbol("EA")
ea.price_point("2022-01-01")  # Will return the price for 2021-12-31
Symbol.max_date_deviation_days = 0
ea.price_point("2022-01-01")  # Will raise a ValueError
```


## Data sources

tessa builds on [yfinance](https://pypi.org/project/yfinance/) and
[pycoingecko](https://github.com/man-c/pycoingecko) and offers **a simplified and
unified interface**. 

Why these two sources? Yahoo Finance (via yfinance) is fast and offers an extensive
database that also contains many non-US markets and many crypto tokens. Coingecko (via
pycoingecko) offers great access to crypto prices, but is limited to 1 year of
historical data. 

More sources can be added in the future. Let me know in the
[issues](https://github.com/ymyke/tessa/issues) of you have a particular request.


## Main submodules

- [symbol](tessa/symbol.html): working with symbols and symbol collections.
- [search](tessa/search.html): searching the different sources.
- [price](tessa/price.html): accessing price functions directly instead of via the
  `Symbol` class.
- [sources](tessa/sources.html): if you'd like to add additional sources to the library.


## How to install

`pip install tessa`

Requires Python 3.10 or higher.


## Prerequisites

See `pyproject.toml`. Major prerequisites are the `yfinance` and `pycoingecko` packages
to access finance information.


## Repository

https://github.com/ymyke/tessa


## On terminology

I'm using symbol instead of ticker because a ticker is mainly used for stock on stock
markets, whereas tessa is inteded to be used for any kind of financial assets, e.g. also
crypto.


## Other noteworthy libraries

- [strela](https://github.com/ymyke/strela): A python package for financial alerts.
- [pypme](https://github.com/ymyke/pypme): A Python package for PME (Public Market
  Equivalent) calculation.